Interpretability

Feature attribution method grounded in cooperative game theory for explaining predictions in tabular settings.

Local surrogate explanation method approximating model behavior near a specific input.

Framework for reasoning about cause-effect relationships beyond correlation, often using structural assumptions and e...

A hidden variable influences both cause and effect, biasing naive estimates of causal impact.

Ensuring model behavior matches human goals, norms, and constraints, including reducing harmful or deceptive outputs.

Automated detection/prevention of disallowed outputs (toxicity, self-harm, illegal instruction, etc.).

Systematic differences in model outcomes across groups; arises from data, labels, and deployment context.

Techniques to understand model decisions (global or local), important in high-stakes and regulated settings.